easystats / easystats/effectsize
Cohen's small/medium/large categories for Epsilon-squared?
Nobody has claimed this yet.
- Dominant language
- R
- Stars
- 353
- Forks
- 25
- Avg merge
- 9h 21m
- Merged PRs (30d)
- 1
Description
Discussed in https://github.com/easystats/effectsize/discussions/679
Originally posted by jarbet August 15, 2025
I often use epsilon-squared ($\epsilon^2$) effect size when doing the Kruskal-Wallis Test. However, I have a question about interpreting the relative size of $\epsilon^2$. The help page of interpret_epsilon_squared says that Cohen's categories are:
However, taking a look at the Cohen 1992 paper, I'm not sure how the above was derived?
Should the cutoffs instead be from line 8 of the above Table, which are 0.02, 0.15, 0.35?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with discussion 679 and the interpret_omega_squared help page linked in the issue. Compare the documented Cohen categories with the cited Cohen 1992 table, then update the relevant interpretation documentation so the epsilon-squared cutoffs and their source are clear.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100